Comparative Modeling of Effective Policies for Colorectal Cancer Control

结直肠癌控制有效政策的比较模型

• 批准号: 10668399
• 负责人: KAREN M KUNTZ
• 金额: $ 112.67万
• 依托单位: SLOAN-KETTERING INST CAN RESEARCH
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-09-08 至 2025-08-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10668399
• 关键词: Address; Age; American Cancer Society; Area; Calibration; Cancer Control; Cancer Etiology; Cessation of life; Clinical; Collaborations; Colonoscopy; Colorectal Cancer; Country; Data; Diagnosis; Effectiveness; Goals; Health Policy; High Performance Computing; Incidence; Income; Intervention; Knowledge; Literature; Methods; Modality; Modeling; Natural History; New Hampshire; Outcome; Pathway interactions; Pattern; Persons; Policies; Population; Population Research; Positioning Attribute; Regimen; Registries; Research; Resources; Role; Seminal; United States; Update; Work; carcinogenesis; colorectal cancer risk; comparative; computer aided detection; deep learning; experience; improved; insight; learning strategy; models and simulation; novel; personalized medicine; personalized screening; population based; prevent; screening; screening program

ABSTRACT Colorectal cancer (CRC) is the second leading cause of cancer death in the United States. The long-term goal of our proposed project is to reduce the population burden of CRC by providing the information needed to address key policy questions across the CRC control continuum in an accessible and transparent manner. To accomplish this goal we will use our population-based microsimulation models to: 1) Evaluate the impact of screening as practiced in the US; 2) Inform the debate about the increase in CRC incidence before age 50; 3) Consider the effectiveness of precision of screening and surveillance; 4) Address other emerging issues and opportunities in CRC control; and 5) Use novel methods to improve model accessibility and transparency. Our team will fill critical gaps in knowledge, enabling decision makers to act. New evidence that we will incorporate in our models to better inform CRC control opportunities will be 1) updated information on screening patterns in the US (in collaboration with the Population-based Research Optimizing Screening through Personalized Regimen, or PROS PR), 2) data on the increased risk of CRC in persons under age 50 (in collaboration with Rebecca Siegal of the American Cancer Society, who did the seminal work in this area), and 3) state-of-the art colonoscopy screening data to incorporate alternative carcinogenesis pathways in the natural history models (in collaboration with the New Hampshire Colonoscopy Registry). We will synthesize and incorporate the growing body of evidence in the literature to assess the clinical utility of personalized screening and treatment, as well as the potential role for novel computer-aided detection and diagnosis modalities. We will expand our models to project clinical and resource-based outcomes for middle-income countries that are considering the implementation of a screening program. Lastly, there is a critical need to make our models assessible and transparent. To this end we will use high performance computing approaches to develop and apply deep-learning methods for model calibration and model emulation, which will aid in model sharing. The three participating modeling groups are well positioned to carry out this work, bringing a wealth of experience, expertise, and insight to issues related to microsimulation modeling of CRC, and have a proven track record of collaboration and disseminating our work to health policy decision makers.

抽象的 结直肠癌（CRC）是美国癌症死亡的第二大原因。我们拟议项目的长期目标是通过以可访问和透明的方式提供解决整个CRC控制连续体中的关键政策问题所需的信息，从而减轻CRC的人口负担。为了实现这一目标，我们将使用基于人群的微观模拟模型来： 1) 评估美国实施的筛查的影响； 2) 为有关 50 岁之前 CRC 发病率增加的争论提供信息； 3）考虑筛查和监测精度的有效性； 4) 解决 CRC 控制中其他新出现的问题和机遇； 5) 使用新颖的方法来提高模型的可访问性和透明度。我们的团队将填补知识方面的关键空白，使决策者能够采取行动。我们将在我们的模型中纳入新的证据，以更好地为 CRC 控制机会提供信息，这些证据将是 1) 有关美国筛查模式的更新信息（与通过个性化方案优化筛查的基于人群的研究或 PROS PR 合作），2) 数据50 岁以下人群罹患 CRC 风险增加的研究（与美国癌症协会的 Rebecca Siegal 合作，她在这一领域做出了开创性的工作），以及 3) 最先进的结肠镜检查筛查数据将替代的致癌途径纳入自然史模型中（与新罕布什尔州结肠镜检查登记处合作）。我们将综合并整合文献中越来越多的证据，以评估个性化筛查和治疗的临床效用，以及新型计算机辅助检测和诊断模式的潜在作用。我们将扩展我们的模型，为正在考虑实施筛查计划的中等收入国家预测临床和基于资源的结果。最后，迫切需要使我们的模型可评估且透明。为此，我们将使用高性能计算方法来开发和应用深度学习方法进行模型校准和模型仿真，这将有助于模型共享。三个参与的建模小组完全有能力开展这项工作，为 CRC 微观模拟建模相关问题带来丰富的经验、专业知识和洞察力，并拥有良好的合作记录和向卫生政策决策者传播我们的工作记录。

项目成果

Characterization and Valuation of the Uncertainty of Calibrated Parameters in Microsimulation Decision Models.

微观模拟决策模型中校准参数不确定性的表征和评估。

• 发表时间: 2022
• 作者: Alarid;Knudsen, Amy B;Ozik, Jonathan;Collier, Nicholson;Kuntz, Karen M
• 通讯作者: Kuntz, Karen M

Colorectal Cancer Screening within Colonoscopy Capacity Constraints: Can FIT-Based Programs Save More Lives by Trading off More Sensitive Test Cutoffs against Longer Screening Intervals?

结肠镜检查能力限制下的结直肠癌筛查：基于 FIT 的计划能否通过牺牲更敏感的测试截止值和更长的筛查间隔来挽救更多生命？

• 发表时间: 2022
• 作者: McFerran, Ethna;O'Mahony, James F;Naber, Steffie;Sharp, Linda;Zauber, Ann G;Lansdorp;Kee, Frank
• 通讯作者: Kee, Frank

Robustness Analysis of Colorectal Cancer Colonoscopy Screening Strategies.

结直肠癌结肠镜检查筛查策略的稳健性分析。

• 发表时间: 2023-03-09
• 作者: de Lima, Pedro Nascimento;Rutter, Carolyn M;Maerzluft, Christopher;Ozik, Jonathan;Collier, Nicholson
• 通讯作者: Collier, Nicholson

Methods for Communicating the Impact of Parameter Uncertainty in a Multiple-Strategies Cost-Effectiveness Comparison.

在多策略成本效益比较中传达参数不确定性影响的方法。

• 发表时间: 2022-10
• 作者: Wolff, Henri B;Qendri, Venetia;Kunst, Natalia;Alarid;Coupé, Veerle M H
• 通讯作者: Coupé, Veerle M H

Emulator-based Bayesian calibration of the CISNET colorectal cancer models.

基于模拟器的 CISNET 结直肠癌模型贝叶斯校准。

• 发表时间: 2024-02-05
• 作者: Pineda;Seguin, Claudia;van Duuren, Luuk A;Knudsen, Amy B;Davidi, Barak;de Lima, Pedro Nascimento;Rutter, Carolyn;Kuntz, Karen M;Lansdorp;Collier, Nicholson;Ozik, Jonathan;Alarid
• 通讯作者: Alarid